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This is an experiment that everyone who learned about cosine distance and vector space information retrieval probably tried, just to see what would happen. "Fu

This is an experiment that everyone who learned about cosine distance and vector space information retrieval probably tried, just to see what would happen. "Fuzzy string matching" isn't really the right term. Of course string distance will give a better fuzzy string match. But this finds words with similar structure rather than words that are similar in the traditional sense. Perhaps there's no obvious application, but it gives results that are very interesting in and of themselves. It might serve to partition search space for another more expensive algorithm.

bede 11y ago
> It might serve to partition search space for another more expensive algorithm This is what we're doing. We're working on approaches for performing nucleotide sequence alignment using approximate time series representations of vectorised DNA sequences. There are some really elegant lower bounding similarity search methods for time series which generate no false negative alignments, allowing use of more expensive alignment algorithms later on in the search to prune out the false positives. We've tested a few transformations including Haar wavelets, DFT and PAA and implemented an indexing structure in C++. Preprint: https://www.academia.edu/12575290/Alignment_by_numbers_sequence_assembly_using_compressed_numerical_representations https://www.academia.edu/12575290/Alignment_by_numbers_seque... (slightly outdated... Email me for more info)